bilibili-transcribe — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited bilibili-transcribe (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
字幕优先:先尝试抓取官方/自动字幕(秒级、免 GPU、免 funasr);抓不到再下载音频用 SenseVoice-Small 转录,存为 Markdown 文件。加 --no-subtitle 可强制走音频转录。
# Python 3.9+
python -m venv .venv
source .venv/bin/activate
# 依赖
pip install funasr modelscope torch torchaudio
# 系统依赖
# macOS: brew install ffmpeg yt-dlp
# Ubuntu: sudo apt install ffmpeg && pip install yt-dlppython scripts/transcribe.py "https://www.bilibili.com/video/BV1rrQGBeEen/"
python scripts/transcribe.py "BV1rrQGBeEen"
python scripts/transcribe.py "BV1rrQGBeEen" --no-subtitle # 强制音频转录B 站有反爬机制,需要加 User-Agent 和 Referer:
yt-dlp --extract-audio --audio-format mp3 --audio-quality 128K \
--user-agent "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) ..." \
--referer "https://www.bilibili.com" \
"https://www.bilibili.com/video/BV1rrQGBeEen/"from funasr import AutoModel
from funasr.utils.postprocess_utils import rich_transcription_postprocess
model = AutoModel(
model="iic/SenseVoiceSmall",
trust_remote_code=True,
vad_model="fsmn-vad",
vad_kwargs={"max_single_segment_time": 30000},
device="cpu",
)
result = model.generate(input=audio_path, language="zh", use_itn=True, batch_size_s=60)自动创建带 frontmatter 的 Markdown 文件。
| 视频时长 | 转录耗时 |
|---|---|
| 5 min | ~10s |
| 10 min | ~20s |
| 30 min | ~60s |
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~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.